The technological advancements in the field of computing are giving rise to the generation of gigantic volumes of data which are beyond the handling capabilities of the conventionally available tools, techniques and systems. These types of data are known as big data. Moreover with the emergence of Internet of Things (IoT), these types of data have increased in multiple folds in 7Vs (volume, variety, veracity, value, variability, velocity and visualisation). There are several techniques prevalent in today’s time for handling these types of huge data. Hadoop is one such open source framework which has emerged as a de facto technology for handling such huge datasets. In an IoT ecosystem, real-time handling of requests is an imperative requirement; however, Hadoop has certain limitations while handling these types of requests. In this article, we present an energy-efficient architecture for effective, secured and real-time handling of IoT big data. The proposed approach adopts atrain distributed system (ADS) to construct the core architecture. This study uses software-defined networking (SDN) framework for energy-efficient and optimal routing of data and requests from source to destination, and vice versa. Furthermore, to ensure secured handling of IoT big data, the proposed approach uses ‘Twofish’ cryptographic technique for encrypting the information captured by the sensors. Finally, the concept of ‘request-type’ identifying unit has been proposed. Instead of handling all the requests in an identical way, the proposed approach works by characterising the requests on the basis of certain criteria and parameters, which are identified here.
Re-Stream: Real-time and energy-efficient resource scheduling in big data stream computing environments